Influence of vibrations on thermodiffusion in binary mixture: A benchmark of numerical solutions
Bibliographic record
Abstract
Double-diffusive and vibrational convection with the Soret effect is considered in a cubic rigid cell filled with water (90%) and isopropanol (10%), subjected to a temperature difference between opposite lateral walls. Numerical simulations are carried out for g-jitter induced flow. The direction of g-jitter is the same as the residual gravity vector, which is perpendicular to the applied temperature gradient. Along with various combinations of static and oscillatory components, vibrations with two different frequencies are examined: (a) when the period of oscillations is smaller than any characteristic time (viscous, thermal, and diffusion), f=0.2Hz; (b) when the period of oscillations is comparable with viscous time, f=0.01Hz. Component separation due to the Soret effect under these driving actions is analyzed. The concept of time-averaged models is applied for the explanation of the high-frequency results. The interplay between the mean and fluctuating motions is discussed. Three research groups performed a benchmark of numerical solutions of three-dimensional Navier-Stokes, energy, and concentration equations using the true physical parameters for a future Space experiment. The objective of this paper is twofold: (i) to carry out an accurate study of heat and mass transfer in a binary liquid with the Soret effect in the presence of steady residual gravity and its oscillatory component; (ii) to carry out a benchmark of numerical solutions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".